coint_ghansen¶

Purpose¶

Computes the tests for the null of no cointegration against the alternative of cointegration with a structural break in the mean.

Format¶

{ ADF_min, TBadf, Zt_min, TBzt, Za_min, TBza, cvADFZt, cvZa } = coint_ghansen(y, x, model[, bwl, ic, pmax, varm, trimm])¶

Parameters:

y (Nx1 matrix) – Dependent variable.
x (NxK matrix) – Independent variable.
model (Scalar) –
Model to be implemented.

1 Level shift (C)

2 Level shift with trend (C/T)

3 Regime shift (C/S)

4 Regime and trend shift
bwl (Scalar) – Optional, bandwidth length for long-run variance computation. Default = round(4 * (T/100)^(2/9)).
ic (Scalar) –
Optional, the information criterion used for choosing lags. Default = 3.

1 Akaike.

2 Schwarz.

3 t-stat significance
pmax (Scalar) – Optional, maximum number of lags for \(\Delta y\) in ADF test. Default = 8.
varm (Scalar) –
Optional, long-run consistent variance estimation method. Default = 1.

1 iid.

2 Bartlett.

3 Quadratic Spectral (QS).

4 SPC with Bartlett (Sul, Phillips & Choi, 2005)

5 SPC with QS

6 Kurozumi with Bartlett

7 Kurozumi with QS
trimm (Scalar) – Optional, trimming rate. Default = 0.10.

Returns:

ADFmin (Scalar) – ADF test statistic
TBadf (Scalar) – Break point using OLS.
Zamin (Scalar) – Za test statistic
TBza (Scalar) – Break point for using Za statistic.
Ztmin (Scalar) – Zt test statistic
TB_zt (Scalar) – Break point using Zt statistic.
cvADFZt (Scalar) – 1%, 5%, 10% critical values for ADF and Zt test statistics.
cvZa (Scalar) – 1%, 5%, 10% critical values for Za test statistics.

Examples¶

new;
cls;
library tspdlib;

// Load dataset
data = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_coint.csv",
                          ". + date($Date, '%b-%y')");

// Define y and x matrix
y = data[., 1];
x = data[., 2:cols(data)];

// Level shift
model = 1;

// Call test
{ ADF_min, TBadf, Zt_min, TBzt, Za_min, TBza, cvADFZt, cvZa } = coint_ghansen(y, x, model);

Source¶

coint_ghansen.src